Skip to main content
SpringerLink
Log in

Heuristic Combined Artificial Neural Networks to Schedule Hybrid Flow Shop with Sequence Dependent Setup Times

  • Conference paper
Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

Included in the following conference series:

Abstract

This paper addresses the problem of arranging jobs to machines in hybrid flow shop in which the setup times are dependent on job sequence. A new heuristic combined artificial neural network approach is proposed. The traditional Hopfield network formulation is modified upon theoretical analysis. Compared with the common used permutation matrix, the new construction needs fewer neurons, which makes it possible to solve large scale problems. The traditional Hopfield network running manner is also modified to make it more competitive with the proposed heuristic algorithm. The performance of the proposed algorithm is verified by randomly generated instances. Computational results of different size of data show that the proposed approach works better when compared to the individual heuristic with random initialization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Okano, H., Davenport, A.J., Trumbo, M., Reddy, C., Yoda, K., Amano, M.: Finishing Line Scheduling in the Steel Industry. Journal of Research & Development 48, 811–830 (2004)

    Google Scholar 

  2. Smith, K.A.: Neural Networks for Combinatorial Optimization: A Review of More Than a Decade of Research. INFORMS Journal on Computing 11 (1999)

    Google Scholar 

  3. Mendes, A., Aguilera, L.: A Hopfield Neural Network Approach to the Single Machine Scheduling Problem. In: Pre-prints of IFAC/Incom98/Information Control In Manufacturing (1998)

    Google Scholar 

  4. Hopfield, J.J., Tank, D.W.: Neural Computation of Decisions in Optimization Problems. Biological Cybernetics 52, 141–152 (1985)

    MATH  MathSciNet  Google Scholar 

  5. Wilson, G.V., Pawley, G.S.: On the Stability of the TSP Algorithm of Hopfield and Tank. Biological Cybernetics 58, 63–70 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  6. Smith, K.A., Palaniswami, M., Krishnamoorthy, M.: Neural Techniques for Combinatorial Optimization with Applications. IEEE Transactions on Neural Networks 9, 1301–1318 (1998)

    Article  Google Scholar 

  7. Smith, K.A., Abramson, D., Duke, D.: Hopfield Neural Networks for Timetabling: Formulations, Methods, and Comparative Results. Computers & Industrial Engineering 44, 283–305 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Systems Engineering, Northeastern University, Shenyang, Liaoning, 110000, China

    Lixin Tang & Yanyan Zhang

Authors
  1. Lixin Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanyan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tang, L., Zhang, Y. (2005). Heuristic Combined Artificial Neural Networks to Schedule Hybrid Flow Shop with Sequence Dependent Setup Times. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_126

Download citation

  • DOI: https://doi.org/10.1007/11427391_126

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation